IEEE

DTSF-CDNet: A Dual-Branch Encoder-Decoder Network with Differential Transformer Skip Fusion for Image Change Detection

Abstract: Change detection plays a vital role in numerous real-world domains, aiming to accurately identify regions that have changed between two temporally distinct images. Capturing the complex ...
GitHub

Transformer From Scratch (PyTorch)

The implementation is intentionally explicit and educational, avoiding high-level abstractions where possible. . ├── config.py # Central configuration file defining model hyperparameters, training ...
Scientific Research Publishing

Explore Anomaly-Aware Transformers for Robust Financial Time Series Forecasting ()

This study investigates whether anomaly-aware modeling can improve stock price forecasting by incorporating signals that highlight unusual market behavior. Financial time series often contain sudden ...
IEEE

Evaluation of Encoder-Only Transformer for Multi-Step Traffic Flow Prediction

Abstract: Traffic flow prediction is critical for Intelligent Transportation Systems to alleviate congestion and optimize traffic management. The existing basic Encoder-Decoder Transformer model for ...
C&EN

Pairwise Attention: Leveraging Mass Differences to Enhance De Novo Sequencing of Mass Spectra

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. A fundamental challenge in mass spectrometry-based proteomics is determining which ...
GitHub

TSDAE layer initialization of encoder and decoder

I want to train pretrain a sentence transformer using TSDAE. We have previously used all-MiniLM-L6-v2 as a checkpoint where we finetuned with MultipleNegativeRankingLoss with the main downstream task ...